Today's supercomputers and cloud systems run many data-centric applications such as machine learning, graph algorithms, and cognitive processing, which have large data footprints and complex data access patterns. With computational capacity of large-scale systems projected to rise up to 50GFLOPS/W, the target energy-per-bit budget for data movement is expected to reach as low as 0.1pJ/bit, assuming 200bits/FLOP for data transfers. This tight energy budget impacts the design of both chip-scale networks and main memory systems. Conventional electrical links used in chip-scale networks (0.5-3pJ/bit) and DRAM systems used in main memory (>30pJ/bit) fail to provide sustained performance at low energy budgets. This thesis builds on the promising research on silicon-photonic technology to design system architectures and system management policies for chip-scale networks and main memory systems. The adoption of silicon-photonic links as chip-scale networks, however, is hampered by the high sensitivity of optical devices towards thermal and process variations. These device sensitivities result in high power overheads at high-speed communications. Moreover, applications differ in their resource utilization, resulting in application-specific thermal profiles and bandwidth needs. Similarly, optically-controlled memory systems designed using conventional electrical-based architectures require additional circuitry for electrical-to-optical and optical-to-electrical conversions within memory. These conversions increase the energy and latency per memory access. Due to these issues, chip-scale networks and memory systems designed using silicon-photonics technology leave much of their benefits underutilized. This thesis argues for the need to rearchitect memory systems and redesign network management policies such that they are aware of the application variability and the underlying device characteristics of silicon-photonic technology. We claim that such a cross-layer design enables a high-throughput and energy-efficient unified silicon-photonic link and main memory system. This thesis undertakes the cross-layer design with silicon-photonic technology in two fronts. First, we study the varying network bandwidth requirements across different applications and also within a given application. To address this variability, we develop bandwidth allocation policies that account for application needs and device sensitivities to ensure power-efficient operation of silicon-photonic links. Second, we design a novel architecture of an optically-controlled main memory system that is directly interfaced with silicon-photonic links using a novel read and write access protocol. Such a system ensures low-energy and high-throughput access from the processor to a high-density memory. To further address the diversity in application memory characteristics, we explore heterogeneous memory systems with multiple memory modules that provide varied power-performance benefits. We design a memory management policy for such systems that allocates pages at the granularity of memory objects within an application.

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Performance unpredictability of the cloud hinders widespread adoption of cloud systems and adversely impacts costs and revenue. To mitigate this challenge, cloud systems typically incorporate monitoring and tracing mechanisms to collect a diverse set of metrics on applications' state to facilitate the analysis of performance fluctuations. Drawing on this collected data, engineers devote considerable effort to diagnosing performance issues and expediting the delivery of superior-quality software to enhance performance, aligning with changing demands. To capture unanticipated performance problems, engineers utilize state-of-the-art diagnostic systems to meticulously trace and record behavior of distributed applications running on cloud. However, this level of detailed tracing incurs considerable costs in terms of storage, computation, and network overheads. Even after engineers have resolved these performance problems, they may face challenges in deploying new code to the cloud. Gradual deployment approaches are available to mitigate risk by enabling faulty versions to be rolled back, but these systems lack the necessary statistical sophistication to accurately assess and compare application versions, potentially leading to further performance issues. This thesis argues that integrating automated, statistically-driven methods is imperative to achieve substantial improvements in efficiency when diagnosing application performance and delivering new code in the cloud. This vision has the potential to enable efficient and proactive performance management beyond the state-of-the-art by reducing time, effort, and cost spent on diagnosis and code delivery. To support this vision, the thesis makes two specific contributions. First, we demonstrate that dynamically adjusting instrumentation using statistically-driven techniques significantly enhances diagnosis efficiency. Our distributed tracing approach enables accurate tracing of sources of performance issues using only a small fraction of the available tracing instrumentation. Second, we demonstrate an online learning-based approach that intelligently adjusts the user traffic split among competing deployments, substantially improves code delivery efficiency. Our online experimentation approach reduces performance variations by directing user traffic to the optimal deployment during code delivery. / 2025-05-24T00:00:00Z

ABSTRACT The objective of this thesis is to study and analyze the feasibility of providing voice access for real-time traffic information. A simulated 8-mile stretch of Interstate-4 will be used as the test model for this particular study. The simulation provides real-time traffic information to a Web Map on the Internet. Since the information is accessed through the Internet, web technologies encompassing VoiceXML is the strong candidate as a method of providing this real-time service. VoiceXML includes automated speech recognition (ASR) and text-to-speech (TTS) capabilities, which accommodate the voice aspect of the research. Therefore, VoiceXML and real-time information will be studied and researched in detail. The thesis will involve development of a web site containing a real-time simulated Web Map of Interstate-4. Web technologies, such as· database, dynamic web languages, and VoiceXML will be used to implement interfaces for access to this service through mobile and conventional telephones. The system will be tested with several users to determine the merit and industrial strength of the integration of the technologies used and applied.

Many healthcare patients are required to enroll in assisted living facilities because they are not able to manage their complex medication regimen without the active assistance of a caregiver. This restricts their ability to live independently, and places a considerable burden on the healthcare system. This thesis describes the development of a system that implements automatic medication management and passive remote monitoring for outpatients. The goal of the system is to enable patients to live independently, while reducing medication noncompliance. The resulting prototype is a device that performs two essential functions: (1) to provide notifications and assistance to the patient when medication is to be taken, and (2) to provide passive monitoring of the patient's compliance to a remote caregiver.